#include <opencv2/ximgproc/structured_edge_detection.hpp>

Collaboration diagram for cv::ximgproc::RFFeatureGetter:

Public Member Functions
virtual void	getFeatures (const Mat &src, Mat &features, const int gnrmRad, const int gsmthRad, const int shrink, const int outNum, const int gradNum) const =0

Public Member Functions inherited from cv::Algorithm
	Algorithm ()

virtual	~Algorithm ()

virtual void	clear ()
	Clears the algorithm state.

virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.

virtual String	getDefaultName () const

virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage.

virtual void	save (const String &filename) const

virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage.

void	write (FileStorage &fs, const String &name) const

Additional Inherited Members
Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file.

template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String.

template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node.

Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Helper class for training part of [P. Dollar and C. L. Zitnick. Structured Forests for Fast Edge Detection, 2013].

Member Function Documentation

virtual void cv::ximgproc::RFFeatureGetter::getFeatures	(	const Mat &	src,
		Mat &	features,
		const int	gnrmRad,
		const int	gsmthRad,
		const int	shrink,
		const int	outNum,
		const int	gradNum ) const

pure virtual

Python:
	cv.ximgproc.RFFeatureGetter.getFeatures(	src, features, gnrmRad, gsmthRad, shrink, outNum, gradNum	) ->	None

This functions extracts feature channels from src. Than StructureEdgeDetection uses this feature space to detect edges.

Parameters

src	: source image to extract features
features	: output n-channel floating point feature matrix.
gnrmRad	: __rf.options.gradientNormalizationRadius
gsmthRad	: __rf.options.gradientSmoothingRadius
shrink	: __rf.options.shrinkNumber
outNum	: __rf.options.numberOfOutputChannels
gradNum	: __rf.options.numberOfGradientOrientations

The documentation for this class was generated from the following file: